Regional brain volumes relate to Alzheimer's disease cerebrospinal fluid biomarkers and neuropsychometry: A cross-sectional, observational study

A causal relationship between panic disorder and risk of alzheimer disease: a two-sample mendelian randomization analysis

BACKGROUND

Observational studies have suggested a link between panic disorder (PD) and Alzheimer disease (AD). This study aimed to identify the underlying association of PD with the risk of AD using Mendelian randomization.

METHODS

Genetic instrumental variables (IVs) were retrieved in the genome-wide association study between PD and AD. Then, five different models, namely inverse variance weighting (IVW), weighted median, weighted mode, MR-Egger and MR-robust adjusted profile scores (MR-RAPS), were used for MR Analysis. Finally, the heterogeneity and pleiotropy of identified IVs were verified by multiple sensitivity tests.

RESULTS

The Cochran's Q test based on MR Egger and IVW showed that no evidence of heterogeneity was found in the effects of instrumental variables, so a fixed-effect model was used. IVW analysis (OR 1.000479, 95% CI [1.000147056, 1.000811539], p = 0.005) indicated that PD was associated with an increased risk of AD, and a causal association existed between them. Meanwhile, weighted median (OR 1.000513373, 95% CI [1.000052145, 1.000974814], p = 0.029) and MR-RAPS (OR 1.000510118, 95% CI [1.000148046, 1.00087232], p = 0.006) also showed the similar findings. In addition, extensive sensitivity analyses confirmed the robustness and accuracy of these results.

CONCLUSION

This investigation provides evidence of a potential causal relationship between PD and the increased risk of AD. Based on our MR results, when diagnosing and treating patients with PD, clinicians should pay more attention to their AD-related symptoms to choose therapeutic measures or minimize comorbidities. Furthermore, the development of drugs that improve both PD and AD may better treat patients with these comorbidities.

Characterizing Treatment Non-responders vs. Responders in Completed Alzheimer's Disease Clinical Trials

Alzheimer's disease (AD) patients have varying responses to AD drugs and there may be no single treatment for all AD patients. Trial after trial shows that identifying non-responsive and responsive subgroups and their corresponding moderators will provide better insights into subject selection and interpretation in future clinical trials. We aim to extensively investigate pre-treatment features that moderate treatment effect of Galantamine, Bapineuzumab, and Semagacestat from completed trial data. We obtained individual-level patient data from ten randomized clinical trials. Six Galantamine trials and two Bapineuzumab trials were from Yale University Open Data Access Project and two Semagacestat trials were from the Center for Global Clinical Research Data. We included a total of 10,948 subjects. The trials were conducted worldwide from 2001 to 2012. We estimated treatment effect using causal forest modeling on each trial. Finally, we identified important pre-treatment features that determine treatment efficacy and identified responsive or nonresponsive subgroups. As a result, patient's pre-treatment conditions that determined the treatment efficacy of Galantamine differed by dementia stages, but we consistently observed that non-responders in Galantamine trials had lower BMI (25 vs 28, P < .001) and increased ages (74 vs 68, P < .001). Responders in Bapineuzumab and Semagacestat trials had lower Aβ42 levels (6.41 vs 6.53 pg/ml, P < .001) and smaller whole brain volumes (983.13 vs 1052.78 ml, P < .001). 6 'positive' treatment trials had subsets of patients who had, in fact, not responded. 4 "negative" treatment trials had subsets of patients who had, in fact, responded. This study suggests that analyzing heterogeneity in treatment effects in "positive" or "negative" trials may be a very powerful tool for identifying distinct subgroups that are responsive to treatments, which may significantly benefit future clinical trial design and interpretation.

Item-Level Scores on the Boston Naming Test as an Independent Predictor of Perirhinal Volume in Individuals with Mild Cognitive Impairment

We explored the methodological value of an item-level scoring procedure applied to the Boston Naming Test (BNT), and the extent to which this scoring approach predicts grey matter (GM) variability in regions that sustain semantic memory. Twenty-seven BNT items administered as part of the Alzheimer's Disease Neuroimaging Initiative were scored according to their "sensorimotor interaction" (SMI) value. Quantitative scores (i.e., the count of correctly named items) and qualitative scores (i.e., the average of SMI scores for correctly named items) were used as independent predictors of neuroanatomical GM maps in two sub-cohorts of 197 healthy adults and 350 mild cognitive impairment (MCI) participants. Quantitative scores predicted clusters of temporal and mediotemporal GM in both sub-cohorts. After accounting for quantitative scores, the qualitative scores predicted mediotemporal GM clusters in the MCI sub-cohort; clusters extended to the anterior parahippocampal gyrus and encompassed the perirhinal cortex. This was confirmed by a significant yet modest association between qualitative scores and region-of-interest-informed perirhinal volumes extracted post hoc. Item-level scoring of BNT performance provides complementary information to standard quantitative scores. The concurrent use of quantitative and qualitative scores may help profile lexical-semantic access more precisely, and might help detect changes in semantic memory that are typical of early-stage Alzheimer's disease.

Cognitive Resilience in Brain Health and Dementia Research

With the expected rise in Alzheimer's disease and related dementias (ADRD) in the coming decades due to the aging population and a lack of effective disease-modifying treatments, there is a need for preventive strategies that may tap into resilience parameters. A wide array of resilience strategies has been proposed including genetics, socioeconomic status, lifestyle modifications, behavioral changes, and management of comorbid disease. These different strategies can be broadly classified as distinguishing between modifiable and non-modifiable risk factors, some of which can be quantified so that their clinical intervention can be effectively accomplished. A clear shift in research focus from dementia risk to addressing disease resistance and resilience is emerging that has provided new potential therapeutic targets. Here we review and summarize the latest investigations of resilience mechanisms and methods of quantifying resilience for clinical research. These approaches include identifying genetic variants that may help identify novel pathways (e.g., lipid metabolism, cellular trafficking, synaptic function, inflammation) for therapeutic treatments and biomarkers for use in a precision medicine-like regimen. In addition, innovative structural and molecular neuroimaging analyses may assist in detecting and quantifying pathological changes well before the onset of clinical symptoms setting up the possibility of primary and secondary prevention trials. Lastly, we summarize recent studies demonstrating the study of resilience in caregivers of persons living with dementia may have direct and indirect impact on the quality of care and patient outcomes.

Culture, Ethnicity, and Level of Education in Alzheimer's Disease

Alzheimer's disease (AD) is the most frequent cause of dementia, where the abnormal accumulation of beta-amyloid (Aβ) and tau lead to neurodegeneration as well as loss of cognitive, behavioral, and functional abilities. The present review analyzes AD from a cross-cultural neuropsychological perspective, looking at differences in culture-associated variables, neuropsychological test performance and biomarkers across ethnic and racial groups. Studies have found significant effects of culture, preferred language, country of origin, race, and ethnicity on cognitive test performance, although the definition of those grouping terms varies across studies. Together, with the substantial underrepresentation of minority groups in research, the inconsistent classification might conduce to an inaccuratte diagnosis that often results from biases in testing procedures that favor the group to which test developers belong. These biases persist even after adjusting for variables related to disadvantageous societal conditions, such as low level of education, unfavorable socioeconomic status, health care access, or psychological stressors. All too frequently, educational level is confounded with culture. Minorities often have lower educational attainment and lower quality of education, causing differences in test results that are then attributed to culture. Higher levels of education are also associated with increased cognitive reserve, a protective factor against cognitive decline in the presence of neurodegeneration. Biomarker research suggests there might be significant differences in specific biomarker profiles for each ethnicity/race in need of accurate cultural definitions to adequately predict risk and disease progression across ethnic/racial groups. Overall, this review highlights the need for diversity in all domains of AD research that lack inclusion and the collection of relevant information from these groups.